Add portfolio experience to a rating table

add_portfolio_experience() enriches a rating_table() object with observed portfolio experience. When data is supplied, observed experience is calculated automatically for all risk factors in the rating table, unless risk_factors is specified. Existing factor_analysis() results can also be supplied through observed.

This makes it possible to compare fitted GLM relativities with observed portfolio patterns in autoplot.rating_table(). The full observed output is stored on the rating table, so autoplot.rating_table() can later switch between metrics such as "frequency", "average_severity" and "risk_premium" without recalculating the summaries.

The observed metric is scaled before plotting. With scale = "reference" the metric is divided by the observed value of the model reference level. If a clear reference level cannot be found, the metric is scaled to its mean. With scale = "mean", the metric is always scaled to its mean.

Usage

add_portfolio_experience(x, ...)

# S3 method for class 'rating_table'
add_portfolio_experience(
  x,
  observed = NULL,
  data = NULL,
  risk_factors = NULL,
  claim_count = NULL,
  exposure = NULL,
  claim_amount = NULL,
  metric = NULL,
  label = "Observed experience",
  color = NULL,
  scale = c("reference", "mean"),
  experience = NULL,
  ...
)

Arguments

x

A rating_table object returned by rating_table().

...

Unused.

observed

Optional factor_analysis() object or list of factor_analysis() objects. If supplied, these observed summaries are attached directly.

data

Optional data.frame. If observed = NULL, observed experience is calculated from this data.

risk_factors

Optional character vector. Risk factors for which observed experience should be calculated. If NULL, all risk factors in the rating table are used.

claim_count

Optional character string. Claim count column used by factor_analysis().

exposure

Optional character string. Exposure column used by factor_analysis().

claim_amount

Optional character string. Claim amount column used by factor_analysis().

metric

Optional character string. Default observed metric to plot. Common choices are "frequency", "severity"/"average_severity" and "risk_premium". The metric can also be overridden in autoplot.rating_table().

label

Character; legend label for the observed experience line.

color

Optional line color. If NULL, the internal risk premium color is used.

scale

Character; scaling applied before plotting. One of "reference" or "mean".

experience

Deprecated alias for observed.

Value

A rating_table object with observed portfolio experience attached.

Author

Martin Haringa

Examples

df <- MTPL2
df$area <- as.factor(df$area)

model <- glm(
  nclaims ~ area + offset(log(exposure)),
  family = poisson(),
  data = df
)

rating_table(model, model_data = df, exposure = "exposure") |>
  add_portfolio_experience(
    data = df,
    claim_count = "nclaims",
    exposure = "exposure"
  ) |>
  autoplot(risk_factors = "area", metric = "frequency")


observed <- factor_analysis(
  df,
  risk_factors = "area",
  claim_count = "nclaims",
  exposure = "exposure"
)

rating_table(model, model_data = df, exposure = "exposure") |>
  add_portfolio_experience(observed = observed) |>
  autoplot(risk_factors = "area")